WO2021109661A1 - 拥塞控制方法以及相关设备 - Google Patents

拥塞控制方法以及相关设备 Download PDF

Info

Publication number
WO2021109661A1
WO2021109661A1 PCT/CN2020/113775 CN2020113775W WO2021109661A1 WO 2021109661 A1 WO2021109661 A1 WO 2021109661A1 CN 2020113775 W CN2020113775 W CN 2020113775W WO 2021109661 A1 WO2021109661 A1 WO 2021109661A1
Authority
WO
WIPO (PCT)
Prior art keywords
congestion control
control parameter
network device
traffic
value
Prior art date
Application number
PCT/CN2020/113775
Other languages
English (en)
French (fr)
Chinese (zh)
Inventor
晏思宇
郑晓龙
邓维山
夏寅贲
Original Assignee
华为技术有限公司
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by 华为技术有限公司 filed Critical 华为技术有限公司
Priority to EP20895560.9A priority Critical patent/EP4054134A4/de
Publication of WO2021109661A1 publication Critical patent/WO2021109661A1/zh
Priority to US17/831,070 priority patent/US20220294736A1/en

Links

Images

Classifications

    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L47/00—Traffic control in data switching networks
    • H04L47/10—Flow control; Congestion control
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L47/00—Traffic control in data switching networks
    • H04L47/10—Flow control; Congestion control
    • H04L47/12—Avoiding congestion; Recovering from congestion
    • H04L47/122—Avoiding congestion; Recovering from congestion by diverting traffic away from congested entities
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L47/00—Traffic control in data switching networks
    • H04L47/10—Flow control; Congestion control
    • H04L47/28—Flow control; Congestion control in relation to timing considerations
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L43/00—Arrangements for monitoring or testing data switching networks
    • H04L43/08—Monitoring or testing based on specific metrics, e.g. QoS, energy consumption or environmental parameters
    • H04L43/0852—Delays
    • H04L43/0864—Round trip delays
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L43/00—Arrangements for monitoring or testing data switching networks
    • H04L43/08—Monitoring or testing based on specific metrics, e.g. QoS, energy consumption or environmental parameters
    • H04L43/0876—Network utilisation, e.g. volume of load or congestion level
    • H04L43/0882—Utilisation of link capacity
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L47/00—Traffic control in data switching networks
    • H04L47/10—Flow control; Congestion control
    • H04L47/11—Identifying congestion
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L47/00—Traffic control in data switching networks
    • H04L47/10—Flow control; Congestion control
    • H04L47/12—Avoiding congestion; Recovering from congestion
    • H04L47/127—Avoiding congestion; Recovering from congestion by using congestion prediction
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L47/00—Traffic control in data switching networks
    • H04L47/10—Flow control; Congestion control
    • H04L47/25—Flow control; Congestion control with rate being modified by the source upon detecting a change of network conditions
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L47/00—Traffic control in data switching networks
    • H04L47/10—Flow control; Congestion control
    • H04L47/29—Flow control; Congestion control using a combination of thresholds

Definitions

  • the embodiments of the present application relate to the field of network control, and in particular, to a congestion control method and related equipment.
  • TCP transmission control protocol
  • RDMA remote direct memory access
  • Congestion indicators mainly include delay, throughput and so on.
  • the congestion control parameters can be obtained through an artificial intelligence (AI) model installed on a network device, and the AI model can be obtained through a large number of historical traffic characteristics training using the initial AI model.
  • AI artificial intelligence
  • the process of using the AI model to obtain congestion control parameters is as follows: the network device collects the traffic characteristics on the network device, such as the egress forwarding rate, queue depth, etc., and the network device sends the collected traffic characteristics to the AI model for online reasoning.
  • the AI model is based on the traffic
  • the feature outputs congestion control parameters to the forwarding chip of the network device. Then, the forwarding chip uses the obtained congestion control parameters to control the flow of the network device.
  • AI models need to be trained from a large number of historical traffic characteristics.
  • the historical traffic characteristics are not extensive enough, the limited historical traffic characteristics cannot completely cover all traffic scenarios, which will lead to congestion control of the AI model output.
  • the parameters are not ideal, so the AI model has insufficient or even inadaptability, that is, the problem of scenario generalization.
  • the embodiments of the present application provide a congestion control method and related equipment, which can improve the scenario generalization of congestion control rules.
  • the first aspect of the embodiments of the present application provides a congestion control method.
  • a first congestion control rule is configured on the network device, and the network device can obtain the first congestion control parameter through the first congestion control rule. After the first device forwards traffic according to the first congestion control parameter, the network device can obtain the first traffic characteristic The first traffic characteristic includes statistical information generated when the first device forwards traffic according to the first congestion control parameter in the first period, and the network device may obtain the first reward value according to the acquired first traffic characteristic. After the network device obtains the first congestion control parameter through the first congestion control rule, the network device can use the first step length to modify the first congestion control parameter to obtain the second congestion control parameter, because the first step length is not equal to 0, so the first step length is not equal to 0. The second congestion control parameter is not equal to the first congestion control parameter.
  • the network device can obtain the second traffic characteristic, which includes the statistical information generated when the first device forwards the traffic according to the second congestion control parameter in the second period , The network device can obtain the second reward value according to the obtained second traffic characteristic.
  • the network device may determine whether the second reward value is greater than the first reward value, and if the network device determines that the second reward value is greater than the first reward value, the network device performs corresponding processing.
  • the network device may obtain the first traffic characteristic, and the first traffic characteristic includes that the first device performs the first congestion control parameter according to the first congestion control parameter in the first period.
  • the first congestion control parameter is obtained according to the first congestion control rule.
  • the network device can obtain the first return value according to the first traffic characteristic.
  • the network device can obtain the second congestion control parameter, and the network device can also obtain the second traffic characteristic.
  • the second traffic characteristic includes the statistical information generated when the first device forwards the traffic according to the second congestion control parameter in the second period.
  • the device can obtain a second reward value according to the second traffic characteristic.
  • the network device executes corresponding processing.
  • the network device uses the first step to modify the first congestion control parameter.
  • a second congestion control parameter that can obtain a larger reward value is obtained. Because the second reward value is greater than the first reward value, the second congestion control parameter is better than the first congestion control parameter. Therefore, the network device has a better response to the first congestion control rule.
  • the inference results have been optimized, and the generalization of the first congestion control rule has been improved.
  • the network device before the network device uses the first step to modify the first congestion control parameter to obtain the second congestion control parameter, the network device can obtain the first operating value and the second operating value of the first device, The first operating value is the operating value of the first device in the target period, and the second operating value is the operating value of the first device in the previous week of the target period.
  • the network device can also obtain the target threshold, which is set in advance The network device determines whether the absolute value of the difference between the first operating value and the second operating value is less than the target threshold. Only when the absolute value of the difference between the first operating value and the second operating value is less than the target threshold, the network device Only the step of using the first step to modify the first congestion control parameter to obtain the second congestion control parameter is performed.
  • the target period refers to the previous period of the first period.
  • the network device before the network device uses the first step to modify the first congestion control parameter and obtains the second congestion control parameter, the network device first determines whether it needs to use the first step to modify the first congestion control parameter, and the network device passes Determine whether the traffic forwarded by the first device tends to be stable to determine whether it is necessary to use the first step to modify the first congestion control parameter.
  • the method for the network device to determine whether the traffic forwarded by the first device tends to stabilize is: the network device obtains the first device For the first operating value and the second operating value in different periods, the network device determines whether the absolute value of the difference between the first operating value and the second operating value is less than the target threshold.
  • the network device determines that the traffic forwarded by the first device is stable, and the network device determines that it needs to use the first step to modify the first congestion control parameter.
  • the network device determines whether the traffic forwarded by the first device is Stable to determine whether it is necessary to use the first step to modify the first congestion control parameter, because when the traffic forwarded by the first device stabilizes, the subsequent modification of the first congestion control parameter by the network device will be more accurate, that is, the network device It can be determined that the result that the second reward value is greater than the first reward value is obtained by the network device using the first step to modify the first congestion control parameter.
  • the network device determines whether the first step of modifying the first congestion control parameter is required by determining whether the traffic forwarded by the first device is stable. Improve the accuracy of the program.
  • the network device can adjust the initial congestion control parameters only through the first congestion control rule, and adjusting the initial congestion control rule only through the first congestion control rule means that the network device does not use the step size to adjust the network device according to the first congestion control rule.
  • a congestion control parameter derived from a congestion control rule the network device directly uses the congestion control parameter derived from the first congestion control rule as a parameter for the first device to control traffic forwarding; the network device uses the first step to modify the first congestion control parameter
  • the network device can count the number of consecutive adjustments that the network device only adjusts the initial congestion control parameter through the first congestion control rule. When the number of consecutive adjustments is greater than the set threshold N, the network device will use the first congestion control parameter. Modify the first congestion control parameter in one step. Accordingly, the first congestion control parameter is obtained by continuously adjusting the initial congestion control parameter N+1 times according to the first congestion control rule.
  • the network device before the network device uses the first step to modify the first congestion control parameter and obtains the second congestion control parameter, the network device can count the continuous adjustment of the network device only through the first congestion control rule to adjust the initial congestion control parameter When the number of consecutive adjustments is greater than the set threshold N, the network device can use the first step to modify the first congestion control parameter.
  • the network device After the network device obtains the congestion control parameter according to the first congestion control rule, the network device It is not necessary to use the step size to modify the congestion control parameters each time, so the network device may not use the step size to adjust the congestion control parameters obtained by the network device according to the first congestion control rule, but directly use the congestion control parameter obtained by the first congestion control rule.
  • the control parameters are used as the parameters for the first device to control traffic forwarding, but the judgment mechanism of the network device may not be perfect.
  • the judgment mechanism of the network device refers to: the network device chooses to use the congestion control parameter after the step size modification as the first device to control the flow forwarding
  • the parameter is still to choose to directly use the congestion control parameter derived from the first congestion control rule as the selection condition of the parameter for the first device to control traffic forwarding; if the judgment mechanism of the network device is not perfect, it may cause the network device to continue to choose to directly congest the first congestion
  • the congestion control parameters derived from the control rules are used as the parameters for the first device to control traffic forwarding, and the congestion control parameters modified by the step size are not selected as the parameters for the first device to control traffic forwarding, that is, the network device does not use the first step length
  • the step of modifying the first congestion control parameter to obtain the second congestion control parameter because when the network device determines that the number of consecutive adjustments is greater than the set threshold N, the network device can use the first
  • Q is the congestion control parameter
  • A is the rate
  • B is the set delay.
  • F(A, B) is a function related to A and B.
  • the first congestion control rule is specifically defined as the first formula, and some parameters in the formula are specifically defined, where A is the rate, B is the set delay, and B is the pre-set value.
  • A is the rate acquired by the network device.
  • the network device can use the acquired rate and the set delay to obtain the congestion control parameters through the first formula. When the acquired rate changes, the congestion control parameters may also change accordingly.
  • the network device obtains different congestion control parameters according to different rates, which realizes the dynamic control of the forwarding traffic by the first device, thereby improving the feasibility of the solution.
  • the relationship between A and B is specifically defined, which improves the feasibility of the solution.
  • the network device uses the first step to modify the first formula to obtain the second formula.
  • the network device uses the first step to modify the first congestion control parameter and obtains the second congestion control parameter
  • the network device uses the first step to modify the first congestion control parameter.
  • the network device uses the first step to modify the first congestion control parameter. In the first formula, the network device not only optimizes the first congestion control parameter derived from the first congestion control rule, but also optimizes the first congestion control rule, so the generalization of the first congestion control rule is improved from the root cause.
  • the network device uses the second formula to obtain the third congestion control parameter according to the acquired second traffic characteristic, and the third congestion control parameter is used by the first device to control the forwarded traffic.
  • the network device can use the second formula to obtain the third congestion control parameter according to the second traffic characteristics, and the third congestion control parameter can be used to control the first congestion control parameter.
  • the congestion index of the first device is improved, and the generalization of the first formula is improved.
  • the first step length is a percentage value.
  • the first step length is a percentage value, because in different traffic models, the value of the first congestion control parameter may vary greatly. If the first step length is a specific value, such as 20, when the first When the congestion control parameter is 1000, the first step to modify the first congestion control parameter will appear too small; when the first congestion control parameter is in the range of 0-30, the first congestion control parameter is 10, and the first step is At 20:00, the modification of the first congestion control parameter in the first step will be too large. Therefore, the first step can use a percentage value to remove the interference caused by the change in the size of the first congestion control parameter itself. Therefore, in practical applications, The first step can be applied to different first congestion control parameters, so the adaptability of the solution in different scenarios is improved, that is, the generalization of the solution is improved.
  • the network device uses the second step size to modify the second congestion control parameter to obtain the third congestion control parameter.
  • the network device can obtain the third traffic characteristic, which includes the statistical information generated when the first device forwards the traffic according to the third congestion control parameter in the third period, and the network device can obtain the statistics according to the To obtain the third flow characteristic, the third return value is obtained.
  • the network device uses the second step to modify the first congestion control parameter forward.
  • the second congestion control parameter is to obtain the third congestion control parameter.
  • the second congestion control parameter is better than the first congestion control parameter.
  • the second congestion control parameter is The control parameters may not be the optimal congestion control parameters.
  • the network device makes further optimization attempts on the basis of the second congestion control parameter, thus increasing the probability of the network device obtaining better congestion control parameters and increasing the first congestion control parameter.
  • the degree of generalization of the control rules is referred to modify the first congestion control parameter forward.
  • the network device can use the third step to reversely modify the second congestion control parameter to obtain the fourth congestion control parameter.
  • the network device can obtain the fourth traffic characteristic, and the fourth traffic characteristic includes the statistical information generated when the first device forwards the traffic according to the fourth congestion control parameter in the fourth cycle, and the network device can obtain the statistics according to the The fourth flow characteristic of the, obtain the fourth return value.
  • the second congestion control parameter is a value.
  • the network device can modify this value to make the second congestion control parameter larger or smaller.
  • the network device attempts to increase or decrease the second congestion control parameter to obtain After the third congestion control parameter, if the third return value is less than the second return value, the network device can determine that the second congestion control parameter is better than the third congestion control parameter, and the network device can determine that the previous attempt to change the second congestion control parameter The behavior of getting bigger or smaller is wrong. Therefore, the network device uses the third step to reversely modify the second congestion control parameter to obtain the fourth congestion control parameter.
  • the reverse modification defined here is only for the purpose of the aforementioned forward modification. Distinguish, unrestricted reverse modification means that the network device performs a reduction operation on the second congestion control parameter.
  • the network device attempts to obtain a third congestion control parameter that is better than the second congestion control parameter and fails.
  • an attempt is made to obtain a fourth congestion control parameter that is better than the second congestion control parameter, thereby increasing the probability that the network device obtains a better congestion control parameter, and increasing the generalization degree of the first congestion control rule.
  • the network device uses the third step to modify the second congestion control parameter to obtain the fourth congestion control parameter. After the first device forwards the traffic according to the fourth congestion control parameter, the network device can obtain the fourth traffic.
  • the fourth traffic characteristic includes statistical information generated when the first device forwards traffic according to the fourth congestion control parameter in the fourth cycle.
  • the network device can obtain the fourth return value according to the acquired fourth traffic characteristic. If the fourth reward value is greater than the second reward value, the network device uses the third step length and the first step length to modify the first congestion control rule to obtain the second congestion control rule.
  • the network device uses the third step size to modify the second congestion control parameter and obtains the fourth congestion control parameter, determines that the fourth return value is greater than the second return value, that is, the fourth congestion control parameter is better than The second congestion control parameter, and the second reward value is greater than the first reward value, that is, the second congestion control parameter is better than the first congestion control parameter.
  • the network device uses the third step length and the first step length to modify the first congestion control Rules, in which, after the network device determines that the fourth congestion control parameter is better than the second congestion control parameter, the network device uses the third step length and the first step length to modify the first congestion control rule, and the network device not only optimizes twice according to the first
  • the first congestion control parameter derived from a congestion control rule also optimizes the first congestion control rule, so the generalization of the first congestion control rule is improved from the root cause.
  • the network device obtains a fourth congestion control parameter that is superior to the second congestion control parameter, and uses the third step length and the first step length to modify the first congestion control rule to obtain the second congestion control parameter. After the rule, the network device uses the second congestion control rule to generate a new congestion control parameter of the first device according to the fourth traffic characteristic, and the new congestion control parameter is used by the first device to control the forwarded traffic.
  • the network device can use the second congestion control rule to obtain the new congestion control parameter according to the fourth traffic characteristic.
  • the control parameter can be used to control the traffic forwarded by the first device, where the network device uses the new congestion control parameter to obtain the new congestion control parameter, that is, the network device uses the second congestion control rule to replace the first congestion control rule, and the first congestion control rule
  • the second congestion control rule is optimized from the first congestion control rule, so the congestion index of the first device is improved, and therefore the generalization of the first congestion control rule is improved.
  • the second step length is greater than the first step length.
  • the second step length is greater than the first step length.
  • the network device uses the first step length to modify the first congestion control parameter, the network device obtains the second congestion control parameter that is better than the first congestion control parameter. This proves the necessity and correctness of the network device to modify the first congestion control parameter. Therefore, the network device can use the second step size greater than the first step size when modifying the second congestion control parameter by the step size, where, Because the second step length is greater than the first step length, within the value range of the congestion control parameter, the network device can determine the optimal congestion control parameter considered by the network device more quickly, thus reducing the convergence time.
  • a third congestion control rule is configured on the network device, and the network device can obtain the fifth congestion control parameter through the third congestion control rule.
  • the network device may obtain the fifth flow characteristic, and the fifth flow characteristic includes the statistical information generated when the second device forwards the flow according to the fifth congestion control parameter in the first period, and the network device may obtain the fifth flow characteristic according to the obtained fifth flow characteristic.
  • the fifth return value after the network device obtains the fifth congestion control parameter through the third congestion control rule, the network device can use the fourth step to modify the fifth congestion control parameter to obtain the sixth congestion control parameter, because the first step is not Equal to 0, so the sixth congestion control parameter is not equal to the fifth congestion control parameter.
  • the network device can obtain the sixth traffic feature, which includes the second device’s In the second cycle, according to the statistical information generated when the traffic is forwarded according to the sixth congestion control parameter, the network device can obtain the sixth return value according to the acquired sixth traffic characteristics; the network device can determine the sum of the sixth return value and the second return Whether it is greater than the sum of the fifth reward value and the first reward value, if the network device determines that the sum of the sixth reward value and the second reward value is greater than the sum of the fifth reward value and the first reward value, the network device performs the corresponding corresponding Processing.
  • the network device may obtain the fifth flow characteristic, and the fifth flow characteristic includes the second device according to the fifth congestion control parameter in the first period. Statistics generated when forwarding traffic.
  • the fifth congestion control parameter is obtained according to the third congestion control rule.
  • the network device can obtain the fifth return value according to the fifth traffic characteristic.
  • the network device can obtain the sixth congestion control parameter, and the network device can also obtain the sixth traffic characteristic.
  • the sixth traffic characteristic includes the statistical information generated when the second device forwards the traffic according to the sixth congestion control parameter in the second period.
  • the device can obtain the sixth reward value according to the sixth traffic characteristic; after the network device obtains the first reward value, the second reward value, the fifth reward value, and the sixth reward value, the network device can determine the sixth reward value and Whether the sum of the second reward is greater than the sum of the fifth reward and the first reward, if the network device determines that the sum of the sixth reward and the second reward is greater than the sum of the fifth reward and the first reward, the network device executes According to the corresponding processing, in the flow control of the network, the flow between the first device and the second device may affect each other. Therefore, the network device comprehensively considers the sum of the return values on the two devices, and the network device uses the second device. Modify the first congestion control parameter in one step to obtain the second congestion control parameter.
  • the network device uses the fourth step to modify the fifth congestion control parameter to obtain the sixth congestion control parameter, because the sixth return value is different from the second return value.
  • the sum is greater than the sum of the fifth return value and the first return value. Therefore, the profit of the network device modifying the first congestion control parameter and the second congestion control parameter this time is positive. Therefore, when the flow control of multiple devices is forwarded, the first The scenario generalization of the first congestion control rule and the second congestion control rule.
  • the network device uses the fourth step to modify the third congestion control rule, the network device uses the first step to modify the first congestion control rule.
  • the network device uses the fourth step to modify the fifth congestion control parameter and obtains the fifth congestion control parameter, determines that the sum of the sixth reward value and the second reward is greater than the fifth reward value and the first reward value.
  • the sum of the return value that is, the comprehensive return value generated by the sixth congestion control parameter and the second congestion control parameter is better than the comprehensive return value of the fifth congestion control parameter and the first congestion control parameter.
  • the network device uses the first step to modify The first congestion control rule, the network device uses the fourth step size to modify the third congestion control rule, wherein the network device is determining that the sum of the sixth reward value and the second reward is greater than the sum of the fifth reward value and the first reward value After that, the network device modifies the first congestion control rule and the third congestion control rule.
  • the network device not only optimizes the first congestion control parameter derived from the first congestion control rule and the fifth congestion control parameter derived from the third congestion control parameter. , It also optimizes the first congestion control rule and the third congestion control rule, so the generalization of the congestion control rule is improved from the root cause.
  • the network device uses the second step size to modify the second congestion control parameter, Obtain the third congestion control parameter, the network device uses the fifth step to modify the sixth congestion control parameter to obtain the seventh congestion control parameter, the first device forwards traffic according to the third congestion control parameter, and the second device according to the seventh congestion control parameter
  • the network device can obtain the third traffic feature and the seventh traffic feature.
  • the third traffic feature includes the statistical information generated when the first device forwards the traffic according to the third congestion control parameter in the third period.
  • the seventh traffic The characteristics include statistical information generated when the second device forwards traffic according to the third congestion control parameter in the third period, the network device obtains a third reward value according to the third traffic characteristic, and obtains a seventh reward value according to the seventh traffic characteristic.
  • the network device uses the second step size to modify the second congestion control parameter to obtain the third Congestion control parameters.
  • the network device uses the fifth step to modify the sixth congestion control parameter to obtain the seventh congestion control parameter.
  • the combined benefit of the sixth congestion control parameter and the second congestion control parameter is greater than that of the fifth congestion control parameter and the first congestion control parameter.
  • the comprehensive benefits of congestion control parameters that is, the return value generated by the combination of the sixth congestion control parameter and the second congestion control parameter is greater than the return value generated by the combination of the fifth congestion control parameter and the first congestion control parameter, and the network equipment is getting better After the combination of the first congestion control parameter and the fifth congestion control parameter, but because the combination of the second congestion control parameter and the sixth congestion control parameter may not be the optimal congestion control parameter combination, the network device is in the second congestion control Further optimization attempts are made on the basis of the combination of the parameters and the sixth congestion control parameter, thus increasing the probability that the network device obtains better than the combination of the second congestion control parameter and the sixth congestion control parameter, and improving the first congestion control rule and the third congestion control parameter.
  • the degree of generalization of congestion control rules is made on the basis of the combination of the parameters and the sixth congestion control parameter, thus increasing the probability that the network device obtains better than the combination of the second congestion control parameter and the sixth congestion control parameter, and improving the first congestion control rule and the third congestion control parameter.
  • the second aspect of the embodiments of the present application provides a congestion control device, which includes multiple functional modules.
  • the multiple functional modules may all be software modules or hardware modules, or a combination of software modules and hardware modules. Modules can be divided differently according to the implementation, and the methods in the above-mentioned first aspect and various implementation modes can be used as the criterion.
  • a third aspect of the embodiments of the present application provides a congestion control device, including a memory and a processor.
  • the memory is used to store a program
  • the processor is configured to execute the program in the memory, so that the congestion control device executes the method described in the first aspect and any one of the implementation manners thereof.
  • the fourth aspect of the embodiments of the present application provides a computer storage medium.
  • the computer storage medium stores instructions.
  • the instructions When the instructions are executed on a computer, the computer executes the first aspect and any one of the implementations described above. The method described in the way.
  • the fifth aspect of the embodiments of the present application provides a computer program product.
  • the computer program product When the computer program product is executed on a computer, the computer executes the method described in the first aspect and any one of its implementation manners.
  • Figure 1 is a schematic diagram of a network framework of an embodiment of the application
  • FIG. 2 is a schematic flowchart of a congestion control method in an embodiment of the application
  • FIG. 3 is a schematic diagram of another flow of a congestion control method in an embodiment of this application.
  • FIG. 4 is another schematic flow chart of the congestion control method in an embodiment of this application.
  • FIG. 5 is a schematic diagram of another flow of the congestion control method in an embodiment of this application.
  • FIG. 6 is a schematic structural diagram of a congestion control device in an embodiment of the application.
  • FIG. 7 is another schematic structural diagram of the congestion control device in an embodiment of the application.
  • Fig. 8 is a schematic structural diagram of a congestion control device in an embodiment of the application.
  • the embodiments of the present application provide a congestion control method and related equipment, which are used in the field of network control, and can improve the generalization of congestion control rules.
  • AI model is an algorithm, which refers to a model that can be solved through input data after training with historical data.
  • the AI model can be either a mainstream deep neural network model or a traditional machine learning model.
  • the network node In the network, when there is traffic passing through a certain network node, the network node will generate flow. In order to maintain the stability of the flow, that is, in order to meet certain conditions, the flow of the network node is controlled.
  • the network node can be a network device, such as a server, a switch, a router, and so on.
  • network technologies such as TCP and RDMA are widely used in wide area networks, data centers and other fields, and these network technologies have higher and higher demands on the network, among which throughput and delay are the main congestion indicators.
  • TCP network devices drop packets according to a drop probability parameter to perform flow control
  • RDMA RDMA network
  • an explicit congestion notification (ECN) waterline is dynamically adjusted to meet throughput and delay.
  • ECN explicit congestion notification
  • the ECN mechanism is widely used in high-performance data center networks based on enhanced RoCE (RDMA over Converged Ethernet), and a reasonable ECN configuration plays a key role in network flow control.
  • the switch has three ECN values that can be configured for the queue, which are the upper line, the lower line, and the maximum mark probability.
  • the two thresholds of the queue length define the marking probability, and the two thresholds are the lower line and the upper line respectively.
  • ECN When the queue length is lower than the threshold waterline, ECN will not be marked, which is equivalent to the actual marking probability of 0; when the queue length exceeds the threshold waterline, all network packets transmitted from the queue will be ECN Marking is equivalent to the actual marking probability of 1.
  • the data packet When the queue length is between two thresholds, the data packet will be ECN marked with a probability of linear growth with the queue length.
  • the switch Take the switch as an example to illustrate the meaning of the ECN mark.
  • the switch is configured with ECN waterline and downline. When the switch port is congested, it will determine whether to mark the packet with ECN according to the ECN threshold.
  • the message generates a congestion notification packet (CNP) message to inform the source end, and the source end network card reduces the occurrence rate according to the number of CNP messages, thereby avoiding congestion.
  • CNP congestion notification packet
  • the diversity of business and network traffic will produce different network traffic models. Under different network traffic models, how network equipment dynamically adjusts and accurately adapts congestion control parameters according to changes in traffic so as to ensure network performance has become an important challenge in the network.
  • the network framework of the embodiment of the present application includes: a network device 101, a first device 102, and a second device 103; wherein, the network device 101 is connected to the first device 102 and the second device 103, respectively.
  • the manner in which the network device 101 is connected to the first device 102 and the manner in which the network device 101 is connected to the second device 103 may be connected through a wired network or through a wireless network.
  • the network device 101 can be connected to more devices.
  • the main function of the network device 101 is to obtain the traffic characteristics of the first device 102 or the first device 102 and the second device 103.
  • the traffic characteristics include the first device 102, or the first device 102 and the second device 103 to forward traffic according to congestion control parameters.
  • the network device 101 uses congestion control rules to generate congestion control parameters according to the acquired traffic characteristics; the network device 101 can also calculate the return value according to the acquired traffic characteristics to evaluate the first device 102 or the first device 102 or the first device 102.
  • the congestion status of the device 102 and the second device 103 is to obtain the traffic characteristics of the first device 102 or the first device 102 and the second device 103.
  • the main function of the first device 102 is to use the acquired congestion control parameters to control the forwarding of traffic, and to generate traffic characteristics according to the forwarding of the traffic.
  • the function of the second device 103 is similar to that of the first device 102.
  • the embodiment of the present application may not have the network device 101.
  • the first device 102 can complete all the functions of the network device 101.
  • the embodiment of the present application may have no network device 101 and no second device 103, the first device 102 does not need to jointly control the forwarding of traffic with the second device 103, and the first device 102 completes all the functions of the network device 101.
  • FIG. 2 is a schematic flowchart of a congestion control method in an embodiment of this application.
  • step 201 the network device obtains a first flow characteristic, and obtains a first reward value according to the first flow characteristic data.
  • the network device is configured with a first congestion control rule.
  • the network device can obtain the first congestion control parameter according to the first congestion control rule, and the network device can obtain the first congestion control parameter according to the first congestion control rule.
  • the network device can obtain the first traffic characteristic.
  • the first traffic characteristic includes the statistical information generated when the first device forwards traffic according to the first congestion control parameter in the first period.
  • the network device can obtain the first traffic characteristic according to the first congestion control parameter. Features, get the first return value.
  • step 202 the network device uses the first step to modify the first congestion control parameter to obtain the second congestion control parameter.
  • the network device uses the first step to modify the first congestion control parameter to obtain the second congestion control parameter, and the second congestion control parameter is not equal to the first congestion control parameter.
  • step 203 the network device obtains a second flow characteristic, and obtains a second reward value according to the second flow characteristic.
  • the network device uses the first step to modify the first congestion control parameter. After obtaining the second congestion control parameter, the network device can obtain the second flow characteristic.
  • the second flow characteristic includes the first device according to the second congestion control parameter in the second period. Based on the statistical information generated when the traffic is forwarded, the network device can obtain the second return value according to the second traffic characteristic.
  • step 204 if the second reward value is greater than the first reward value, the network device performs corresponding processing.
  • the network device can determine whether the second reward value is greater than the first reward value. If the network device determines that the second reward value is greater than the first reward value, the network device executes the corresponding Processing.
  • the network device can perform a variety of different processing.
  • the processing under such conditions is collectively referred to as corresponding processing in this application.
  • the corresponding processing performed by the network device may be regarded as a corresponding operation of accepting the modification of the first congestion control parameter.
  • the network device may obtain the first flow characteristic, and the first flow characteristic includes the first device according to the first congestion control parameter in the first period.
  • the first congestion control parameter is obtained according to the first congestion control rule.
  • the network device can obtain the first return value according to the first traffic characteristic.
  • the network device can obtain the second congestion control parameter, and the network device can also obtain the second traffic characteristic.
  • the second traffic characteristic includes the statistical information generated when the first device forwards the traffic according to the second congestion control parameter in the second period.
  • the device can obtain a second reward value according to the second traffic characteristic.
  • the network device executes corresponding processing.
  • the network device uses the first step to modify the first congestion control parameter.
  • a second congestion control parameter that can obtain a larger reward value is obtained. Because the second reward value is greater than the first reward value, the second congestion control parameter is better than the first congestion control parameter. Therefore, the network device has a better response to the first congestion control rule. The inference result is optimized, thus improving the generalization of the first congestion control rule.
  • the first congestion control parameter may be one parameter, and the first congestion control parameter may also be multiple parameters, which are described separately below.
  • the first congestion control parameter is a parameter.
  • FIG. 3 is a schematic flowchart of another embodiment of the congestion control method provided by this application.
  • step 301 the network device obtains the first congestion control parameter.
  • the network device is configured with the first congestion control rule.
  • the first congestion control rule is the first formula.
  • the network device can input the collected flow characteristics into the first formula to obtain the first formula.
  • the first congestion control parameter output by a formula in order to facilitate the understanding of the congestion control method in this embodiment, this embodiment uses the following formula as the first formula:
  • Q is the congestion control parameter
  • A is the rate
  • B is the set delay
  • Rate A can be the forwarding rate of the first device or a certain queue of the first device.
  • the forwarding rate is a type of traffic characteristic.
  • the traffic characteristic refers to the statistical information generated when the first device forwards traffic, such as the number of outgoing message bytes. , Number of outgoing packets, queue depth, number of packets marked by ECN, throughput information, number of lost packets, etc.
  • the set delay B is a value set in advance.
  • the congestion control configuration personnel of the first device can set the value of the set delay based on experience or a template.
  • the value of the set delay reflects the configuration personnel’s Delay requirements in the congestion indicator of the device.
  • the specific process of obtaining the first congestion control parameter can be as follows: the network device collects the rate A of the first device in the previous cycle, obtains the preset set delay B, and then sets the rate A and the set delay B into the first Formula to obtain the first congestion control parameter Q.
  • the network device can use the pre-set rate, or not acquire the first congestion control parameter in this cycle, wait for the next cycle to acquire the rate in this cycle, and use the rate in this cycle.
  • the rate obtains the first congestion control parameter to control the flow of the first device in the next cycle.
  • the first congestion control parameter may be the marking probability and the discarding probability.
  • the first congestion control rule may be an AI model.
  • an AI model may be selected as the first congestion control rule.
  • this embodiment takes the first congestion control rule as the first formula as an example for description.
  • the network device may be the first device, or may be a device other than the first device.
  • the network device obtains the first traffic characteristic, the first traffic characteristic includes the statistical information generated when the first device forwards the traffic according to the first congestion control parameter in the first period, and the network device obtains the first traffic characteristic according to the first traffic characteristic. A return value.
  • the network device can obtain the first flow characteristic.
  • the first flow characteristic includes the data generated when the first device forwards the flow according to the first congestion control parameter in the first period.
  • the first traffic characteristic can specifically be the statistical information of the first device, or the statistical information of the port of the first device, or the statistical information of the queue of the first device; the network device can obtain the first return according to the first traffic characteristic value.
  • the first device uses the first congestion control parameter to control the traffic forwarded by the first device in the first period, and the first device uses the second congestion control parameter to control the traffic in the first period.
  • the traffic forwarded by the first device is controlled in the second cycle.
  • the first traffic feature includes the statistical information generated when the first device uses the first congestion control parameter to forward traffic in the first cycle.
  • the second traffic feature includes the first device in the first cycle. The statistical information generated when the first congestion control parameter is used to forward traffic within a week, and so on.
  • the period duration of the first period and the second period may be the same or different.
  • the first period and the second period may have an interval, may be adjacent, or may overlap.
  • the network device can obtain the first traffic characteristic, which may be a value at a certain moment in the first cycle , It may also be a processed value.
  • the first flow characteristic may be an average value in the first period.
  • the network device when the network device is the first device, the network device directly issues the first congestion control parameter to the forwarding chip, so that the forwarding chip uses the first congestion control parameter to control the traffic forwarded by the first device in the first cycle.
  • the network device when the network device is a device other than the first device, after the network device obtains the first congestion control parameter, the network device sends the first congestion control parameter to the first device, so that the first device is in the first cycle
  • the first congestion control parameter is used to control the traffic forwarded by the first device in the first cycle.
  • Congestion indicators will include multiple indicators, such as latency and throughput. In order to facilitate the evaluation of the pros and cons of the first device's different cycles of congestion indicators, the multiple indicators are integrated into one indicator. This indicator is Return value.
  • the first flow characteristic undergoes preprocessing to obtain throughput or delay.
  • the queue depth may be converted into delay through preprocessing, for example, when the first flow characteristic is the outgoing text
  • the number of knots can be preprocessed to convert the number of bytes of the outgoing message into a throughput, and then the first return value can be calculated according to the throughput or delay obtained after the preprocessing.
  • the network device can use the following algorithm to obtain the first return value:
  • R is the first return value
  • J is throughput
  • K is delay
  • m and n are weighting coefficients.
  • the network device can use the following algorithm to obtain the first return value:
  • R is the first return value
  • J is the throughput
  • K is the delay
  • m and n are the weighting coefficients
  • L is the service performance index
  • v is the weighting coefficient.
  • the network device obtains the first operating value and the second operating value of the first device, and determines whether the difference between the first operating value and the second operating value is less than a target threshold.
  • the target threshold is a value set in advance.
  • the network device can use the first step to modify the first congestion control parameter.
  • the first operating value is the forwarding rate of the first device in the target period
  • the target period refers to the previous period of the first period
  • the second operating value is the forwarding rate of the first device in one week before the target period.
  • the first operating value is the forwarding rate of the first queue of the first device in the target period
  • the second operating value is the forwarding rate of the first queue of the first device in a week before the target period.
  • the first running value is the queue depth of the first queue of the first device in the target period
  • the target period refers to the previous period of the first period
  • the first running value is the first queue of the first device in the target period.
  • the target threshold may also be different.
  • the target threshold is the first threshold
  • the first operating value is that of the first device
  • the target threshold is the second threshold
  • the first threshold is not equal to the second threshold.
  • the network device may adjust the initial congestion control parameter only through the first congestion control rule, and adjusting the initial congestion control rule only through the first congestion control rule means that the network device does not use the step size to adjust the network device according to the first congestion control rule.
  • the network device directly uses the congestion control parameter obtained by the first congestion control rule as the parameter for the first device to control traffic forwarding; the network device uses the first step to modify the first congestion control parameter to obtain the second congestion control parameter.
  • the network device may count the number of consecutive adjustments of the initial congestion control parameter by the network device only through the first congestion control rule.
  • step 304 if the difference between the first operating value and the second operating value is less than the target threshold, the network device uses the first step to forwardly modify the first congestion control parameter to obtain the second congestion control parameter.
  • the network device uses the first step to forwardly modify the first congestion control parameter to obtain the second congestion control parameter.
  • the forward modification is only to distinguish it from the reverse modification described later. It does not mean that the first congestion control parameter can only be added forward.
  • the first congestion control parameter is 100
  • the first step length is 20, and the network device
  • the second congestion control parameter can be 80 or 120.
  • the second congestion control parameter is 120 is taken as an example for description.
  • the first step length is a percentage value, because in the network, the first congestion control parameter may vary greatly. If the first step length is a specific value, such as 20, when the first congestion control parameter is 1000, The first step is too small to modify the first congestion control parameter. Therefore, the first step can use a percentage value to remove the interference caused by the change of the first congestion control parameter. When the first congestion control parameter is 100, the first step When the length is 20%, the network device uses the first step to forwardly modify the first congestion control parameter, and the obtained second step can be 80 or 120.
  • the target threshold can be adjusted according to the size of the network fluctuation of the first device.
  • the network device reduces the target threshold.
  • the network fluctuates greatly, that is, the traffic of the first device changes greatly, and the network device increases the target threshold.
  • the network device may not obtain the first operating value and the second operating value of the first device, and the network device It can be determined whether the number of consecutive adjustments is greater than the set threshold N.
  • the network device executes the first long forward modification of the first congestion control parameter to obtain the second congestion. Steps to control parameters.
  • the network device executes the step of using the first step to forwardly modify the first congestion control parameter to obtain the second congestion control parameter, which includes the following situations:
  • the network device executes the first step of forward modification of the first congestion control parameter , The step of obtaining the second congestion control parameter.
  • the network device executes the first step of forward modification of the first congestion control parameter , The step of obtaining the second congestion control parameter.
  • the network device executes the first step of forward modification of the first congestion control parameter , The step of obtaining the second congestion control parameter.
  • step 303 may not be performed.
  • the network device may not need to confirm that the difference between the first operating value and the second operating value is less than the target threshold, and directly Use the first step to forwardly modify the first congestion control parameter to obtain the second congestion control parameter.
  • the network device obtains a second flow characteristic, and the second flow characteristic includes the statistical information generated when the first device forwards the flow according to the second congestion control parameter in the second period; the network device according to the second flow characteristic, Obtain the second return value.
  • the network device uses the first step to positively modify the first congestion control parameter.
  • the network device can obtain the second flow characteristic.
  • the second flow characteristic includes the first device according to the first congestion control parameter in the second period.
  • the second congestion control parameter is the statistical information generated when the traffic is forwarded.
  • the second traffic characteristic may specifically be the statistical information of the first device, or the statistical information of the port of the first device, or the statistical information of the queue of the first device; the network device obtains the first device’s statistical information.
  • the network device can obtain a second reward value according to the acquired second traffic characteristic, and the algorithm of the second reward value is similar to the algorithm of the first reward value in step 302.
  • the second flow characteristic may be the value of the first device at a certain moment in the second period, or a processed value.
  • the second flow characteristic may be the average value of the first device in the second period.
  • the network device when the network device is the first device, the network device directly issues the second congestion control parameter to the forwarding chip, so that the forwarding chip controls the traffic forwarded by the first device in the second cycle.
  • the network device when the network device is a device other than the first device, after the network device obtains the second congestion control parameter, the network device sends the second congestion control parameter to the first device for the first device to use The second congestion control parameter controls the traffic forwarded by the first device in the second cycle.
  • step 306 the network device confirms whether the second reward value is greater than the first reward value.
  • the network device After the network device obtains the second reward value and the first reward value, the network device confirms whether the second reward value is greater than the first reward value.
  • step 307 if the second reward value is greater than the first reward value, the network device uses the first step to modify the first formula to obtain the second formula, and uses the second formula to obtain the congestion control parameter.
  • the network device uses the first step to modify the first formula to obtain the second formula, and uses the second formula to obtain the congestion control parameter.
  • the second formula may be the following formula:
  • Q is the congestion control parameter
  • A is the rate
  • B is the set delay
  • C1 is the first step of the percentage value.
  • the network device uses the rate of the first device in the first cycle to set the delay and the first step length, and the congestion control parameter can be obtained through the second formula.
  • the congestion control parameter is used as the first congestion control parameter
  • the second formula is used as the congestion control parameter. For the first formula, return to step 302.
  • the network device determines that the second reward value is greater than the first reward value, the network device does not need to modify the first formula in the first step to obtain the second formula, but uses the second step to continue forward modification
  • the second congestion control parameter obtains the third congestion control parameter, and the network device obtains the third flow characteristic, and the third flow characteristic includes the statistical information generated when the first device forwards the flow according to the third congestion control parameter in the third period;
  • the network device obtains the third return value according to the third traffic characteristic; if the third return value is greater than the second return value, the network device continues to use the third step to modify the third congestion control parameter forward to obtain the fourth congestion control parameter,
  • the network device obtains a fourth traffic characteristic, and the fourth traffic characteristic includes statistical information generated when the first device forwards traffic according to the fourth congestion control parameter in the fourth period; the network device obtains a fourth return value according to the fourth traffic characteristic , And so on, until the T+1 reward value is less than the T reward value, the network device uses the first step, the second step, and the sum of
  • step 308 if the second reward value is less than the first reward value, the network device uses the second step size to reversely modify the first congestion control parameter to obtain the third congestion control parameter.
  • the network device uses the second step size to reversely modify the first congestion control parameter to obtain the third congestion control parameter.
  • the reverse modification is just to distinguish it from the forward modification described above. It does not mean that the first congestion control parameter can only be reduced in the reverse direction.
  • the first congestion control parameter is 100
  • the second step is 20
  • the network device After using the second step to reversely modify the first congestion control parameter, the third congestion control parameter can be 80 or 120.
  • the third congestion control parameter is 80 is taken as an example for description.
  • the second step length can be equal to the first step length, for example, the first step length is 20%, and the second step length can also be 20%.
  • step 309 the network device obtains a third traffic characteristic, where the third traffic characteristic includes statistical information generated when the first device forwards traffic according to the third congestion control parameter in the third period; the network device according to the third traffic characteristic, Obtain the third return value.
  • the network device uses the first step to reversely modify the first congestion control parameter. After obtaining the third congestion control parameter, the network device obtains the third flow characteristic.
  • the third flow characteristic includes the first device according to the third congestion control parameter in the third period.
  • the congestion control parameter generates statistical information when forwarding traffic.
  • the third traffic feature can specifically be the statistical information of the first device, or the statistical information of the port of the first device, or the statistical information of the queue of the first device; the network device obtains the third After the traffic characteristics are performed, the network device may obtain a third reward value according to the acquired third traffic characteristics, and the algorithm of the third reward value is similar to the algorithm of the first reward value in step 302.
  • step 310 the network device confirms whether the third reward value is greater than the first reward value.
  • the network device After the network device obtains the third reward value and the first reward value, the network device confirms whether the third reward value is greater than the first reward value.
  • step 311 if the third reward value is greater than the first reward value, the network device uses the second step size to modify the first formula to obtain a second formula, and uses the second formula to obtain a new congestion control parameter.
  • the network device uses the second step size to modify the first formula to obtain the second formula, and uses the second formula to obtain the congestion control parameter.
  • the second formula may be the following algorithm:
  • Q is the congestion control parameter
  • A is the rate
  • B is the set delay
  • C2 is the second step of the percentage value.
  • the network device uses the rate of the first device in the second cycle to set the delay and the first step length.
  • the congestion control parameter can be obtained through the second formula.
  • the congestion control parameter is regarded as the first congestion control parameter, and the second formula is regarded as For the first formula, return to step 302.
  • the network device determines that the third reward value is greater than the first reward value, the network device does not need to modify the first formula in the first step to obtain the second formula, but uses the third step to continue the reverse modification.
  • the third congestion control parameter obtains the fourth congestion control parameter, the network device obtains the fourth flow characteristic, and the fourth flow characteristic includes the statistical information generated when the first device forwards the flow according to the fourth congestion control parameter in the fourth period;
  • the network device obtains the fourth return value according to the fourth traffic characteristic; if the fourth return value is greater than the third return value, the network device continues to use the fourth step to reversely modify the fourth congestion control parameter to obtain the fifth congestion control parameter,
  • the network device obtains a fifth traffic characteristic, and the fifth traffic characteristic includes statistical information generated when the first device forwards traffic according to the fifth congestion control parameter in the fifth period; the network device obtains a fifth return value according to the fifth traffic characteristic , And so on, until the T+1th reward value is less than the Tth reward value, the network device will take the first step, the second step
  • step 312 if the third reward value is less than the first reward value, the network device uses the third step size to modify the first congestion control parameter forward to obtain the fourth congestion control parameter.
  • the network device uses the third step size to forward modify the first congestion control parameter to obtain the fourth congestion control parameter.
  • the third step length is greater than the first step length, because after the network device modifies the first congestion control parameter forward and reversely, the second reward value and the third reward value obtained are both smaller than the first reward value, then There is a probability of falling into a local optimum.
  • the first congestion control parameter is 100
  • the second congestion control parameter is 120
  • the second congestion control parameter is 80.
  • the probability is between 80 and 120.
  • the optimal solution is around 100.
  • the third step length should be greater than the first step length.
  • step 313 the network device obtains a fourth flow characteristic, where the fourth flow characteristic includes statistical information generated when the first device forwards traffic according to the fourth congestion control parameter in the fourth cycle; the network device obtains the fourth flow characteristic according to the fourth flow characteristic, Obtain the fourth return value.
  • the network device uses the third step to modify the first congestion control parameter in the forward direction. After obtaining the fourth congestion control parameter, the network device obtains the fourth flow characteristic.
  • the fourth flow characteristic includes the first device in the fourth cycle according to the fourth Congestion control parameters generate statistical information when forwarding traffic.
  • the fourth traffic feature can specifically be statistical information of the first device, or statistical information of the port of the first device, or statistical information of the queue of the first device; the network device obtains the fourth After the traffic characteristics are performed, the network device can obtain a fourth reward value according to the acquired fourth traffic characteristics, and the algorithm of the fourth reward value is similar to the algorithm of the first reward value in step 302.
  • step 314 the network device confirms whether the fourth reward value is greater than the first reward value.
  • the network device After the network device obtains the fourth reward value and the first reward value, the network device confirms whether the fourth reward value is greater than the first reward value.
  • step 315 if the fourth reward value is greater than the first reward value, the network device uses the third step size to modify the first formula to obtain a second formula, and uses the second formula to obtain a new congestion control parameter.
  • the network device uses the third step size to modify the first formula to obtain the second formula, and uses the second formula to obtain the new congestion control parameter.
  • the second formula may be the following algorithm:
  • Q is the congestion control parameter
  • A is the rate
  • B is the set delay
  • C3 is the third step of the percentage value.
  • the network device uses the rate of the first device in the fourth cycle to set the delay and the first step length.
  • the congestion control parameter can be obtained through the second formula.
  • the congestion control parameter is regarded as the first congestion control parameter, and the second formula is regarded as For the first formula, return to step 302.
  • the network device determines that the fourth reward value is greater than the first reward value, the network device does not need to modify the first formula with the third step length to obtain the step of obtaining the second formula, but uses the fourth step to continue forward modification
  • a fourth congestion control parameter a fifth congestion control parameter is obtained, a network device obtains a fifth flow characteristic, and the fifth flow characteristic includes statistical information generated when the first device forwards traffic according to the fifth congestion control parameter in the fifth cycle;
  • the network device obtains the fifth return value according to the fifth traffic characteristic; if the fifth return value is greater than the fourth return value, the network device continues to use the fifth step to modify the fifth congestion control parameter forward to obtain the sixth congestion control parameter,
  • the network device obtains a sixth traffic characteristic, and the sixth traffic characteristic includes statistical information generated when the first device forwards traffic according to the sixth congestion control parameter in the sixth period; the network device obtains a sixth return value according to the sixth traffic characteristic , And so on, until the T+1 reward value is less than the T reward value, the network device will take the first step, the
  • step 316 if the fourth reward value is less than the first reward value, the network device uses the fourth step to reversely modify the first congestion control parameter to obtain the fifth congestion control parameter.
  • the network device uses the fourth step to reversely modify the first congestion control parameter to obtain the fifth congestion control parameter.
  • the fourth step size is greater than the second step size, because after the network device modifies the first congestion control parameter forward and reversely, the second reward value and the third reward value obtained are both less than the first reward value, then There is a probability of falling into a local optimum.
  • the first congestion control parameter is 100
  • the second congestion control parameter is 120
  • the second congestion control parameter is 80.
  • the probability is between 80 and 120.
  • the optimal solution is around 100.
  • the fourth step length should be greater than the second step length.
  • step 317 the network device obtains a fifth flow characteristic, where the fifth flow characteristic includes statistical information generated when the first device forwards traffic according to the fifth congestion control parameter in the fifth period; the network device obtains the fifth flow characteristic according to the fifth flow characteristic, Obtain the fifth return value.
  • the network device uses the fourth step to reversely modify the first congestion control parameter. After obtaining the fifth congestion control parameter, the network device obtains the fifth flow characteristic.
  • the fifth flow characteristic includes the first device according to the fifth Congestion control parameters generate statistical information when forwarding traffic.
  • the fifth traffic feature can specifically be statistical information of the first device, or statistical information of the port of the first device, or statistical information of the queue of the first device; the network device obtains the fifth After the traffic characteristic is performed, the network device can obtain a fifth reward value according to the acquired fifth traffic characteristic, and the algorithm of the fifth reward value is similar to the algorithm of the first reward value in step 302.
  • step 318 the network device confirms whether the fifth reward value is greater than the first reward value.
  • the network device After the network device obtains the fifth reward value and the first reward value, the network device confirms whether the fifth reward value is greater than the first reward value.
  • step 319 if the fifth reward value is greater than the first reward value, the network device uses the fourth step size to modify the first formula to obtain the second formula, and uses the second formula to obtain the new congestion control parameter.
  • the network device uses the fourth step size to modify the first formula to obtain the second formula, and uses the second formula to obtain the congestion control parameter.
  • the second formula may be the following algorithm:
  • Q is the congestion control parameter
  • A is the rate
  • B is the set delay
  • C4 is the fourth step of the percentage value.
  • the network device uses the rate of the first device in the fifth cycle to set the delay and the first step length.
  • the congestion control parameter can be obtained through the second formula.
  • the congestion control parameter is regarded as the first congestion control parameter, and the second formula is regarded as For the first formula, return to step 302.
  • the network device determines that the fifth reward value is greater than the first reward value, the network device does not need to modify the first formula with the fourth step length to obtain the step of obtaining the second formula, but uses the fifth step length to continue the reverse modification
  • a fifth congestion control parameter, a sixth congestion control parameter is obtained, a network device obtains a sixth flow characteristic, and the sixth flow characteristic includes statistical information generated when the first device forwards traffic according to the sixth congestion control parameter in the sixth cycle;
  • the network device obtains the sixth return value according to the sixth traffic characteristic; if the sixth return value is greater than the fifth return value, the network device continues to use the sixth step to reversely modify the sixth congestion control parameter to obtain the seventh congestion control parameter,
  • the network device obtains the seventh traffic characteristic, and the seventh traffic characteristic includes the statistical information generated when the first device forwards traffic according to the seventh congestion control parameter in the seventh cycle; the network device obtains the seventh return value according to the seventh traffic characteristic , And so on, until the T+1th reward value is less than the Tth reward value, the network device will take
  • step 320 if the fifth return value is greater than the first return value, there is a F% probability that the network device will use the third step size as the first step size and the fourth step size as the second step size, and return to step 312 , The network device has a probability of G% and returns to step 301.
  • step 312 the network device has a hundred percent probability. The probability of dividing G is returned to step 301.
  • F plus G equals 100.
  • the value of F decays with the number of times of returning to step 312, for example, the first time F is equal to 50, after step 320, it returns to step 312, from step 312 to step 320, the value of F becomes 40, then In this determination, there is a 40% probability that it will return to step 312.
  • the first congestion control parameter is multiple parameters.
  • the first congestion control parameter includes three parameters, namely the lower line, the upper line, and the maximum marking probability.
  • FIG. 4 is another flow diagram of the congestion control method provided by this application.
  • step 401 the network device obtains a first congestion control parameter.
  • the network device is configured with the first congestion control rule.
  • the first congestion control rule is the AI model.
  • the network device can input the collected initial flow characteristics into the AI model to obtain the AI model
  • the output first congestion control parameter, the first congestion control parameter includes the first downline, the first upline, and the first maximum marking probability.
  • the network device can use the pre-set traffic characteristic as the initial traffic characteristic, or do not acquire the first congestion control parameter in this cycle, and wait for the next cycle to acquire the traffic of the current cycle.
  • the characteristic is used as the initial flow characteristic, and the first congestion control parameter is obtained by using the flow characteristic of the current cycle to control the flow of the first device in the next cycle.
  • the first congestion control rule can also be a formula.
  • a formula can be selected as the first congestion control rule.
  • this embodiment takes the first congestion control rule being an AI model as an example for description.
  • the network device may be the first device, or may be a device other than the first device.
  • the network device obtains a first traffic characteristic
  • the first traffic characteristic includes the statistical information generated when the first device forwards traffic according to the first congestion control parameter in the first period, and the network device obtains the first traffic characteristic according to the first traffic characteristic.
  • a return value A return value.
  • the network device obtains the first operating value and the second operating value of the first device, and determines whether the difference between the first operating value and the second operating value is less than a target threshold.
  • Step 402 and step 403 are similar to step 302 and step 303 in the aforementioned FIG. 3.
  • step 404 if the difference between the first operating value and the second operating value is less than the target threshold, the network device uses the first step to forwardly modify the first downline to obtain the second downline.
  • the network device uses the first long step to modify the first downline to obtain the second downline, and the network device transfers the second downline to the second downline.
  • the line, the first water line, and the first maximum marking probability are used as the second congestion control parameters, and other descriptions are similar to step 304 in FIG. 3 described above.
  • step 405 the network device obtains a second traffic characteristic, and the second traffic characteristic includes statistical information generated when the first device forwards traffic according to the second congestion control parameter; the network device obtains a second return value according to the second traffic characteristic .
  • Step 405 is similar to step 305 in FIG. 3 described above.
  • step 406 the network device positively modifies the first upper waterline by using the second step size to obtain the second forward waterline.
  • the network device uses the second step to modify the first upstream waterline forward to obtain the second forward waterline.
  • the network device uses the target downstream waterline, the second forward waterline, and the first maximum marking probability as the third congestion control parameter.
  • the target downline includes the first downline or the second positive downline. If the second return value is greater than the first downline, the target downline includes the second downline, and if the second return value is greater than the first downline ,
  • the target launch line includes the first launch line.
  • the network device can use the second step to modify the second forward downward pipeline to obtain the third forward downward pipeline, and the network device can set the third forward downward pipeline ,
  • the first water line and the first maximum marking probability are used as the third congestion control parameter, and the network device obtains the third traffic characteristic, and the third traffic characteristic includes that the first device forwards the traffic according to the third congestion control parameter in the third period
  • the network device using the first long forward modification is inferior to the first downward pipeline, and the network device uses the second positive downward pipeline.
  • the AI model inputs the same initial flow characteristics, reduce the probability that the AI model will output the second positive downward pipeline.
  • the initial flow characteristics are 50
  • the AI model outputs the first downline 10, the first upline 60, and the probability of the first maximum marking probability 50 is 30%.
  • the AI model outputs the second positive downline 12, the first upline 30, and the first The probability of the maximum marking probability of 50 is 7%.
  • the network equipment modifies the AI model.
  • the AI model When the AI model inputs the initial flow characteristics of 50, the AI model outputs the second positive downward waterline 12, the first upper waterline 30, and the first maximum marking probability 50 The probability is 3%. Therefore, the next time the network device obtains the initial traffic characteristics 50 and uses the AI model to reason about the congestion control parameters, the AI model outputs the second forward downward pipeline 12, the first upward pipeline 30, and the probability of the first maximum marking probability 50 will decrease. .
  • the network device uses the second step to modify the first waterline forward and the network device uses the second step to modify the second positive downward waterline.
  • There is a second step in the second step but this second step is only a convenience
  • the description does not limit the values of the two second step lengths to be equal, similar, in this embodiment, even if the same step length appears, it is necessary to determine whether the object of step length modification is the same, only the step length is the same, and Only when the target of step modification is the same can it be determined that the values of the two steps are the same.
  • the network device uses the second step to positively modify the first waterline.
  • the modified object is the first waterline, and the network device uses the first waterline.
  • Two-step forward modification of the second positive downward waterline The object of modification is the second forward downward waterline, so the values of these two steps may be different.
  • the network device obtains a third traffic characteristic, and the third traffic characteristic includes statistical information generated when the first device forwards traffic according to the third congestion control parameter; the network device obtains a third return value according to the third traffic characteristic .
  • the network device obtains a third traffic characteristic, where the third traffic characteristic includes statistical information generated when the first device forwards traffic according to the third congestion control parameter; the network device obtains a third return value according to the third traffic characteristic.
  • step 408 the network device uses the third step size to forwardly modify the first maximum marking probability to obtain the second forward maximum marking probability.
  • the network equipment uses the third step to modify the first maximum marking probability forward to obtain the second forward maximum marking probability; the network equipment uses the target launch line, the target upload line and the second maximum marking probability as the fourth congestion control parameter, the target The downline includes the first downline or the second positive downline. If the second return value is greater than the first downline, the target downline includes the second downline.
  • the target lower line includes the first lower line
  • the target upper line includes the first upper line or the second positive upper line
  • the third return value is greater than the first return value
  • the third return value is greater than the second return value
  • the target waterline includes the second positive waterline, otherwise the target waterline includes the first waterline.
  • the network device may use the third step to modify the second forward waterline in a positive direction.
  • the network device obtains a fourth flow characteristic, where the fourth flow characteristic includes statistical information generated when the first device forwards the flow according to the fourth congestion control parameter; the network device obtains a fourth return value according to the fourth flow characteristic .
  • the network device obtains a fourth flow characteristic, where the fourth flow characteristic includes statistical information generated when the first device forwards the flow according to the fourth congestion control parameter; the network device obtains a fourth return value according to the fourth flow characteristic.
  • step 410 the network device uses the fourth step size to reversely modify the first downline to obtain the second reverse downline.
  • the network equipment uses the fourth step to reversely modify the first offline to obtain the second reverse offline.
  • the network equipment uses the second reverse offline, the target upstream, and the target maximum marking probability as the fifth congestion control parameter,
  • the target upper waterline includes the first upper waterline or the second positive upper waterline.
  • the target upper waterline includes the second positive upper waterline Water line, otherwise the target water line includes the first water line, the target maximum marking probability includes the first maximum marking probability or the second forward maximum marking probability, if the fourth reward value is greater than the third reward value, and the fourth reward value If it is greater than the second reward value and the fourth reward value is greater than the first reward value, the target maximum marking probability includes the second forward maximum marking probability, otherwise the target maximum marking probability includes the first maximum marking probability.
  • the network device can use the fourth step size
  • the second forward maximum mark probability is modified in the forward direction.
  • the network device obtains a fifth flow characteristic, and the fifth flow characteristic includes statistical information generated when the first device forwards the flow according to the fifth congestion control parameter; the network device obtains a fifth return value according to the fifth flow characteristic .
  • the network device obtains a fifth flow characteristic, where the fifth flow characteristic includes statistical information generated when the first device forwards the flow according to the fifth congestion control parameter; the network device obtains a fifth return value according to the fifth flow characteristic.
  • step 412 the network device uses the fifth step to reversely modify the first water line to obtain the second reverse water line.
  • the network device uses the fifth step to reversely modify the first upper waterline to obtain the second reverse upper waterline.
  • the network device uses the reverse target offline, the second reverse upper waterline, and the maximum marking probability of the target as the sixth congestion control parameter ,
  • the reverse target launch line includes the target launch line or the second reverse launch line, if the fifth return value is greater than the fourth return value, and the fifth return value is greater than the third return value, and the fifth return value is greater than the second return value ,
  • the fifth reward value is greater than the first reward value
  • the reverse target pipeline includes the second reverse pipeline, otherwise the reverse target pipeline includes the target pipeline, and the target maximum marking probability includes the first maximum marking probability or the second Maximum positive mark probability.
  • the target maximum mark probability includes the second positive maximum Marking probability, otherwise the target maximum marking probability includes the first maximum marking probability.
  • step 406 if the fifth reward value is greater than the fourth reward value, and the fifth reward value is greater than the third reward value, and the fifth reward value is greater than the second reward value, and the fifth reward value is greater than the first reward value.
  • the network device can use the fifth step to reversely modify the second reverse pipeline.
  • the network device obtains a sixth traffic characteristic, where the sixth traffic characteristic includes statistical information generated when the first device forwards traffic according to the sixth congestion control parameter; the network device obtains a sixth return value according to the sixth traffic characteristic .
  • the network device obtains a sixth traffic characteristic, where the sixth traffic characteristic includes statistical information generated when the first device forwards traffic according to the sixth congestion control parameter; the network device obtains a sixth return value according to the sixth traffic characteristic.
  • step 414 the network device uses the sixth step size to reversely modify the first maximum marking probability to obtain the second reverse maximum marking probability.
  • the network equipment uses the sixth step to reversely modify the first maximum marking probability to obtain the second reverse maximum marking probability.
  • the network equipment takes the reverse target offline, the reverse target upstream, and the second reverse maximum marking probability as the first Seven congestion control parameters, the reverse target launch line includes the target launch line or the second reverse launch line, if the fifth return value is greater than the fourth return value, and the fifth return value is greater than the third return value, and the fifth return value is greater than The second return value, and the fifth return value is greater than the first return value, then the reverse target lower line includes the second reverse lower line, otherwise the reverse target lower line includes the target lower line, and the reverse target upper line includes the target upper line Water line or second reverse upper water line, if the sixth reward value is greater than the fifth reward value, and the sixth reward value is greater than the fourth reward value, and the sixth reward value is greater than the third reward value, and the sixth reward value is greater than the first Two return values, and the sixth return value is greater than the first return value, then the reverse target upper waterline includes the second reverse upper waterline,
  • the network device can use the sixth step to reversely modify the second reverse upper waterline.
  • the network device obtains the seventh traffic characteristic, the seventh traffic characteristic includes the statistical information generated when the first device forwards the traffic according to the seventh congestion control parameter; the network device obtains the seventh return value according to the seventh traffic characteristic .
  • the network device obtains the seventh traffic characteristic, where the seventh traffic characteristic includes the statistical information generated when the first device forwards the traffic according to the seventh congestion control parameter; the network device obtains the seventh return value according to the seventh traffic characteristic.
  • step 416 the network device obtains the new initial flow characteristics, and the network device inputs the new initial flow characteristics into the AI model for inference, and obtains the initial congestion control parameters.
  • the network device obtains new initial traffic characteristics, and the network device inputs the new initial traffic characteristics into the AI model for inference, and obtains initial congestion control parameters.
  • the initial congestion control parameters are used to allow the first device to control the forwarded traffic according to the initial congestion control parameters.
  • the network device does not need to use the step size to modify the initial congestion control parameter, and directly uses the initial congestion control parameter as a parameter for the first device to control traffic forwarding.
  • the network device uses the seventh congestion control parameter to modify the AI model, and the network device uses the modified AI model to perform Reasoning to obtain the initial congestion control parameters.
  • the seventh congestion control parameter includes reverse target launch line, reverse target launch line, and reverse target maximum marking probability.
  • the reverse target launch line includes the target launch line or the second reverse launch line.
  • the reverse target pipeline includes the second reverse pipeline, otherwise the reverse target pipeline includes the target pipeline, and the target pipeline includes the first pipeline or the second forward pipeline
  • the lower line if the second return value is greater than the first return value, the target lower line includes the second forward lower line, and if the second return value is greater than the first return value, the target lower line includes the first lower line; reverse The target upper waterline includes the target upper waterline or the second reverse upper waterline.
  • the reverse target upper waterline includes the second reverse upper waterline, otherwise the reverse target upper waterline includes the target upper waterline,
  • the target upper waterline includes the first upper waterline or the second positive upper waterline.
  • the target upper waterline includes the second positive upper waterline Waterline, otherwise the target upper waterline includes the first upper waterline; the maximum reverse target marking probability includes the target maximum marking probability or the second reverse maximum marking probability; if the seventh reward value is greater than the sixth reward value, and the seventh reward Value is greater than the fifth reward value, and the seventh reward value is greater than the fourth reward value, and the seventh reward value is greater than the third reward value, and the seventh reward value is greater than the second reward value, and the seventh reward value is greater than the first reward value ,
  • the reverse target maximum marking probability includes the second reverse maximum marking probability, otherwise the reverse target maximum marking probability includes the target maximum marking probability, and the target maximum marking probability includes the first maximum marking probability or the second forward maximum marking probability, if If the fourth reward value is greater than the third reward value, and the fourth reward value is greater than the second reward value, and the fourth reward value is greater than the first reward value, then the target maximum marking probability includes the second positive maximum marking
  • the AI model when the AI model inputs the same initial traffic characteristics, increase the probability that the AI model will output the seventh congestion control parameter.
  • the initial traffic characteristics are 50
  • the AI model input the initial traffic characteristics 50 to the AI model, and the AI model outputs the first one.
  • Waterline 10 the first upper waterline 60
  • the probability of the first maximum marking probability 50 is 30%
  • the AI model outputs the seventh congestion control parameter: the second forward downward pipeline 12, the second reverse downward pipeline 27, and the second The probability of the maximum forward marking probability of 60 is 7%.
  • the network equipment modifies the AI model.
  • the AI model inputs the initial traffic characteristics of 50
  • the AI model outputs the seventh congestion control parameter: the second forward downward pipeline is 12, and the second reverse launch Line 27, the probability of the second maximum marking probability 60 in the positive direction is 50%.
  • the AI model outputs the seventh congestion control parameter: the second forward downward pipeline 12, the second reverse downward pipeline 27, and the second forward pipeline.
  • the probability of reaching the maximum mark probability of 60 will increase, from 7% to 50%.
  • step 406 if the seventh reward value is greater than the sixth reward value, and the seventh reward value is greater than the fifth reward value, and the seventh reward value is greater than the fourth reward value, and the seventh reward value is greater than the third reward value. If the reward value is greater than the second reward value, and the seventh reward value is greater than the first reward value, the network device can use the seventh step to reversely modify the second reverse maximum marking probability.
  • a single device in addition to the network device, can use the congestion control method to control the flow forwarded by the device, or multiple devices can use the congestion control method to control the flow forwarded by the device.
  • the situation of a single device is described above, and the situation of multiple devices is described below.
  • FIG. 5 is a schematic flowchart of another embodiment of the congestion control method provided by this application.
  • step 501 the network device obtains the first congestion control parameter and the second congestion control parameter.
  • the network device is configured with the first congestion control rule. When the network device needs to control the flow of the first device, the network device can use the first congestion control rule to obtain the first congestion according to the first initial flow characteristics collected from the first device. control parameter.
  • the network device is also configured with a second congestion control rule. When the network device needs to control the flow of the second device, the network device can use the second congestion control rule to obtain the second congestion control rule according to the second initial flow characteristics collected from the second device. Congestion control parameters.
  • the network device can use the pre-set flow characteristic as the initial flow characteristic, or not obtain the first congestion control parameter and the second congestion control parameter in this cycle, and wait for the next Periodically obtain the flow characteristics of the current period as the initial flow characteristics, use the flow characteristics of the first device in the current period to obtain the first congestion control parameter to control the flow of the first device in the next period, and use the flow characteristics of the second device in the current period to obtain the first The second congestion control parameter controls the flow of the second device in the next cycle.
  • the first congestion control rule can be an AI model, and the first congestion control rule can also be a formula. In practical applications, one can be selected as the first congestion control rule.
  • step 502 the network device obtains the first flow characteristic and the second flow characteristic, the network device obtains a first reward value according to the first flow characteristic, and obtains a second reward value according to the second flow characteristic.
  • the network device obtains the first traffic characteristic and the second traffic characteristic.
  • the first traffic characteristic includes the statistical information generated when the first device forwards traffic according to the first congestion control parameter in the first period.
  • the network device obtains the first traffic characteristic according to the first traffic characteristic.
  • a return value, the second traffic characteristic includes statistical information generated when the second device forwards traffic according to the second congestion control parameter in the first period, and the network device obtains the second return value according to the second traffic characteristic.
  • the method for obtaining the reward value is similar to the method for obtaining the reward value in step 302 of FIG. 3 described above, and the details are not repeated here.
  • the network device obtains the first operating value and the second operating value of the first device, obtains the third operating value and the fourth operating value of the second device, and determines whether the average value of the difference is less than the target threshold.
  • the network device obtains the first operating value and the second operating value of the first device, obtains the third operating value and the fourth operating value of the second device, and determines whether the average value of the difference is less than the target threshold.
  • the average value of the difference refers to the first The average value of the difference value and the second difference value.
  • the first difference value refers to the difference value between the first operation value and the second operation value
  • the second difference value is the difference value between the third operation value and the fourth operation value.
  • the network device may adjust the initial congestion control parameter only through the first congestion control rule, and adjusting the initial congestion control rule only through the first congestion control rule means that the network device does not use the step size to adjust the network device according to the first congestion control rule.
  • the network device directly uses the congestion control parameter obtained by the first congestion control rule as the parameter for the first device to control traffic forwarding; the network device uses the first step to modify the first congestion control parameter to obtain the second congestion control parameter.
  • the network device may count the number of consecutive adjustments of the initial congestion control parameter by the network device only through the first congestion control rule.
  • step 504 if the mean value of the difference is less than the target threshold, the network device uses the first step to forwardly modify the first congestion control parameter to obtain the third congestion control parameter, and the network device uses the second step to forwardly modify the second congestion control parameter. Congestion control parameters to obtain the fourth congestion control parameter.
  • the network device uses the first step to forwardly modify the first congestion control parameter to obtain the third congestion control parameter, and the network device uses the second step to forwardly modify the second congestion control parameter to obtain The fourth congestion control parameter.
  • the forward modification is only to distinguish it from the reverse modification described later. It does not mean that the first congestion control parameter can only be added forward.
  • the first congestion control parameter is 100
  • the first step length is 20, and the network device
  • the second congestion control parameter can be 80 or 120.
  • the second congestion control parameter is 120 is taken as an example for description.
  • the first step length and the second step length are percentage values.
  • the target threshold can be adjusted according to the size of the network fluctuation of the first device.
  • the network device reduces the target threshold.
  • the network fluctuates greatly, that is, the traffic of the first device changes greatly, and the network device increases the target threshold.
  • the network device may not obtain the first operating value and the second operating value of the first device, and the network device may Determine whether the number of consecutive adjustments is greater than the set threshold N.
  • the network device executes the first long forward modification of the first congestion control parameter to obtain the second congestion control Parameter steps.
  • the network device when the network device counts the number of consecutive adjustments of the initial congestion control parameter by the network device only through the first congestion control rule, the network device obtains the first operating value, the second operating value, the third operating value, and the fourth operating value. At the operating value, as long as one condition is met, the network device executes the step of using the first step to forwardly modify the first congestion control parameter to obtain the second congestion control parameter, which includes the following situations:
  • the network device executes the first step of forward modification of the first congestion control parameter , The step of obtaining the second congestion control parameter.
  • the network device executes the first step of forward modification of the first congestion control parameter , The step of obtaining the second congestion control parameter.
  • the network device executes the first step of forward modification of the first congestion control parameter , The step of obtaining the second congestion control parameter.
  • step 503 may not be performed.
  • the network device does not need to confirm whether the mean value of the difference is less than the target threshold, and directly uses the first long forward Modify the first congestion control parameter to obtain the second congestion control parameter, and use the second step size to modify the second congestion control parameter forward to obtain the fourth congestion control parameter.
  • step 505 the network device obtains the third flow characteristic and the fourth flow characteristic, the network device obtains the third reward value according to the third flow characteristic, and the network device obtains the fourth reward value according to the fourth flow characteristic.
  • the network device uses the first step to positively modify the first congestion control parameter.
  • the network device can obtain a third flow characteristic.
  • the third flow characteristic includes the first device according to the first congestion control parameter in the second period.
  • Three congestion control parameters are the statistical information generated when the traffic is forwarded; the third traffic feature can specifically be the statistical information of the first device, or the statistical information of the port of the first device, or the statistical information of the queue of the first device; the network device obtains the first device’s statistical information.
  • the network device can obtain a third reward value according to the acquired third flow characteristic, and the algorithm of the third reward value is similar to the algorithm of the first reward value in step 302 in FIG. 3 described above.
  • the third flow characteristic may be a value of the first device at a certain moment in the second period, or a processed value.
  • the third flow characteristic may be an average value of the first device in the second period.
  • the network device uses the second step to modify the second congestion control parameter forward. After obtaining the fourth congestion control parameter, the network device can obtain the fourth flow characteristic.
  • the fourth flow characteristic includes the second device according to the second congestion control parameter in the second period.
  • the fourth congestion control parameter is the statistical information generated when the traffic is forwarded; the fourth traffic feature may specifically be the statistical information of the second device, or the statistical information of the port of the second device, or the statistical information of the queue of the second device; the network device obtains the first
  • the network device can obtain a fourth reward value according to the acquired fourth flow characteristic.
  • the algorithm of the fourth reward value is similar to the algorithm of the first reward value in step 302 in FIG. 3 described above.
  • the fourth flow characteristic may be the value of the second device at a certain moment in the second period, or a processed value. For example, the fourth flow characteristic may be the average value of the second device in the second period.
  • the network device when the network device is the first device, the network device directly issues the third congestion control parameter to the forwarding chip, so that the forwarding chip controls the traffic forwarded by the first device in the second period, and the network device sends the first device to the second device.
  • the fourth congestion control parameter is used to allow the second device to control the forwarded traffic according to the fourth congestion control parameter.
  • the network device when the network device is the second device, the network device directly issues the fourth congestion control parameter to the forwarding chip, so that the forwarding chip controls the traffic forwarded by the second device in the second period, and the network device sends the first device to the first device.
  • the third congestion control parameter is used to allow the third device to control the forwarded traffic according to the third congestion control parameter.
  • the network device when the network device is a device other than the first device and the second device, after the network device obtains the third congestion control parameter and the fourth congestion control parameter, the network device sends the third congestion control parameter to the first device
  • the parameter is used to allow the first device to use the third congestion control parameter to control the traffic forwarded by the first device in the second cycle.
  • the network device will also send the fourth congestion control parameter to the second device for the second device to use the Four congestion control parameters are used to control the traffic forwarded by the second device in the second cycle.
  • step 506 the network device confirms whether the sum of the third reward value and the fourth reward value is greater than the sum of the first reward value and the second reward value.
  • step 507 if the sum of the third reward value and the fourth reward value is greater than the sum of the first reward value and the second reward value, the network device uses the first step to modify the first congestion control rule to obtain the third congestion control Rule, use the second step to modify the second congestion control rule to obtain the fourth congestion control rule.
  • the network device determines that the sum of the third reward value and the fourth reward value is greater than the sum of the first reward value and the second reward value, the network device does not need to modify the first congestion control rule in the first step to obtain the first congestion control rule.
  • Three congestion control rules use the second step size to modify the second congestion control rule to obtain the fourth congestion control rule step, but use the third step size to continue to modify the third congestion control parameter forward to obtain the fifth congestion control parameter, Use the fourth step to continue to modify the fourth congestion control parameter in the forward direction to obtain the sixth congestion control parameter;
  • the network device obtains the fifth flow characteristic, and the fifth flow characteristic includes the first device according to the fifth congestion control in the third cycle Parameter forwarding traffic;
  • the network device obtains the sixth traffic characteristic, and the sixth traffic characteristic includes the statistical information generated when the second device forwards the traffic according to the sixth congestion control parameter in the third period;
  • the network device obtains the statistics according to the sixth congestion control parameter;
  • Five flow characteristics obtain the fifth return value; the network device obtains the sixth return value according to the
  • the network equipment uses the first step length, the third step length, and the sum of all the step lengths to the T-1 step length as the first step length, and uses the first step length to modify the first congestion control Rule, obtain the third congestion control rule
  • the network device uses the second step, the fourth step, and the sum of all the steps to the T-th step as the second step, and uses the second step to modify the second congestion control Rule to obtain the fourth congestion control rule.
  • step 508 if the sum of the third reward value and the fourth reward value is less than the sum of the first reward value and the second reward value, the network device uses the fifth step to reversely modify the first congestion control parameter to obtain the fifth Congestion control parameters, use the sixth step size to modify the first congestion control parameter to obtain the sixth congestion control parameter.
  • step 509 the network device obtains the fifth flow characteristic and the sixth flow characteristic, the network device obtains the fifth reward value according to the fifth flow characteristic, and the network device obtains the sixth reward value according to the sixth flow characteristic.
  • the network device uses the third step to reversely modify the first congestion control parameter.
  • the network device can obtain the fifth flow characteristic.
  • the fifth flow characteristic includes the first device according to the first congestion control parameter in the third period.
  • the fifth congestion control parameter is the statistical information generated when the traffic is forwarded; the fifth traffic feature may specifically be the statistical information of the first device, or the statistical information of the port of the first device, or the statistical information of the queue of the first device; the network device obtains the first
  • the network device can obtain a fifth reward value according to the acquired fifth flow characteristic, and the algorithm of the fifth reward value is similar to the algorithm of the first reward value in step 302 in FIG. 3 described above.
  • the fifth flow characteristic may be the value of the first device at a certain moment in the third period, or a processed value.
  • the fifth flow characteristic may be the average value of the first device in the third period.
  • the network device uses the fourth step to reversely modify the second congestion control parameter.
  • the network device can obtain the sixth flow characteristic.
  • the sixth flow characteristic includes the second device according to the second congestion control parameter in the third cycle.
  • the statistical information generated when the congestion control parameter forwards the traffic can specifically be the statistical information of the second device, or the statistical information of the port of the second device, or the statistical information of the queue of the second device; the network device obtains the first
  • the network device can obtain a sixth reward value according to the acquired sixth traffic characteristic, and the algorithm of the sixth reward value is similar to the algorithm of the first reward value in step 302 in FIG. 3 described above.
  • the sixth flow characteristic may be the value of the second device at a certain moment in the third period, or a processed value.
  • the sixth flow characteristic may be the average value of the second device in the third period.
  • step 510 if the sum of the fifth reward value and the sixth reward value is greater than the sum of the first reward value and the second reward value, the network device uses the fifth step to modify the first congestion control rule to obtain the third congestion control Rule, use the sixth step to modify the second congestion control rule to obtain the fourth congestion control rule.
  • the network device determines that the sum of the fifth reward value and the sixth reward value is greater than the sum of the first reward value and the second reward value, the network device does not need to modify the fifth step length first.
  • a congestion control rule, the third congestion control rule is obtained, the second congestion control rule is modified by the sixth step, and the fourth congestion control rule is obtained, but the seventh step is used to continue to modify the fifth congestion control parameter in the reverse direction, Obtain the seventh congestion control parameter, continue to modify the sixth congestion control parameter in the reverse direction using the eighth step size, and obtain the eighth congestion control parameter.
  • the congestion control method in the embodiment of the present application is described above, and the congestion control apparatus in the embodiment of the present application is described below.
  • FIG. 6 is a schematic structural diagram of an embodiment of the congestion control apparatus provided by this application.
  • the first acquiring unit 601 is configured to acquire a first traffic characteristic, where the first traffic characteristic includes statistical information generated when the first device forwards traffic according to the first congestion control parameter in the first cycle, and the first congestion control parameter is based on the first congestion control parameter. Obtained by congestion control rules;
  • the second obtaining unit 602 is configured to obtain the first reward value according to the first traffic characteristic
  • the third obtaining unit 603 is configured to modify the first congestion control parameter by using the first step to obtain the second congestion control parameter;
  • the fourth acquiring unit 604 is configured to acquire a second traffic characteristic, where the second traffic characteristic includes statistical information generated when the first device forwards traffic according to the second congestion control parameter in the second period;
  • the fifth obtaining unit 605 is configured to obtain a second return value according to the second flow characteristic
  • the execution unit 606 is configured to execute corresponding processing if the second reward value is greater than the first reward value.
  • the first obtaining unit 601 may obtain the first flow characteristic, and the first flow characteristic includes the first device according to the first congestion in the first period.
  • the first congestion control parameter is obtained according to the first congestion control rule, and the second obtaining unit 602 can obtain the first return value according to the first traffic characteristic.
  • the third obtaining unit 603 can obtain the second congestion control parameter, and the fourth obtaining unit 604 can obtain the second flow characteristic.
  • the second flow characteristic includes the first device according to the second congestion in the second period.
  • the statistical information generated when the control parameter forwards the traffic can obtain the second reward value according to the second traffic characteristic, and if the second reward value is greater than the first reward value, the execution unit 606 executes corresponding processing, wherein ,
  • the third obtaining unit 603 uses the first step to modify the first congestion control parameter, and obtains the second congestion control parameter that can obtain a larger reward value. Because the second reward value is greater than the first reward value, the second congestion control parameter It is better than the first congestion control parameter, so the congestion control device optimizes the inference result of the first congestion control rule, thereby improving the generalization of the first congestion control rule.
  • each unit of the congestion control apparatus is similar to those described in the foregoing embodiment shown in FIG. 2 and will not be repeated here.
  • FIG. 7 is a schematic structural diagram of another embodiment of the congestion control apparatus provided by this application.
  • the congestion control device provided in this application further includes:
  • the first obtaining unit 601 is further configured to obtain the first operating value and the second operating value of the first device.
  • the congestion control device also includes:
  • the determining unit 707 is configured to determine whether the difference between the first operating value and the second operating value is less than a target threshold
  • the third acquiring unit 603 is specifically configured to, if the difference value is less than the target threshold, execute the step of using the first step to modify the first congestion control parameter to obtain the second congestion control parameter.
  • the congestion control device further includes:
  • the adjustment unit 708 is configured to adjust initial congestion control parameters
  • the statistics unit 709 is used to count the number of consecutive adjustments of initial congestion control parameters
  • the third obtaining unit 603 is specifically configured to perform the step of modifying the first congestion control parameter by using the first step length to obtain the second congestion control parameter when the number of consecutive adjustments is greater than the set threshold N;
  • the first congestion control parameter is obtained by continuously adjusting the initial congestion control parameter N times according to the first congestion control rule.
  • the first congestion control rule is a first formula, and the first formula is:
  • Q F(A, B), where Q is the congestion control parameter, A is the rate, B is the set delay, and F(A, B) is the function related to A and B.
  • the fifth obtaining unit 605 is further configured to modify the first formula by using the first step length to obtain the second formula.
  • the fifth obtaining unit 605 is further configured to obtain the third congestion control parameter by using a second formula according to the second traffic characteristic;
  • the third congestion control parameter is used for the first device to control the forwarded traffic.
  • the first step length is a percentage value.
  • the second formula is:
  • the execution unit 606 is specifically configured to use the second step size to forward modify the second congestion control parameter to obtain the third congestion control parameter;
  • the execution unit 606 is specifically configured to obtain a third traffic characteristic, where the third traffic characteristic includes statistical information generated when the first device forwards traffic according to the third congestion control parameter in the third period;
  • the execution unit 606 is specifically configured to obtain the third reward value according to the third traffic characteristic.
  • the third obtaining unit 603 is further configured to, if the third reward value is less than the second reward value, use the third step size to reversely modify the second congestion control parameter to obtain the fourth congestion control parameter;
  • the fourth acquiring unit 604 is further configured to acquire a fourth traffic characteristic, where the fourth traffic characteristic includes statistical information generated when the first device forwards traffic according to the fourth congestion control parameter in the fourth cycle;
  • the fifth obtaining unit 605 is further configured to obtain a fourth reward value according to the fourth traffic characteristic.
  • the congestion control device further includes:
  • the modifying unit 710 is configured to, if the fourth reward value is greater than the second reward value, modify the first congestion control rule by using the third step length and the first step length to obtain the second congestion control rule.
  • the congestion control device further includes:
  • the generating unit 711 is configured to use the second congestion control rule to generate a new congestion control parameter of the first device according to the fourth traffic characteristic, and the new congestion control parameter is used for the first device to control the forwarded traffic.
  • the second step length is greater than the first step length.
  • the first obtaining unit 601 is further configured to obtain a fifth flow characteristic, and the fifth flow characteristic includes statistical information generated when the second device forwards traffic according to the fifth congestion control parameter in the first cycle, and the fifth congestion control parameter Obtained according to the third congestion control rule;
  • the second obtaining unit 602 is further configured to obtain a fifth return value according to the fifth flow characteristic
  • the third obtaining unit 603 is further configured to modify the fifth congestion control parameter by using the fourth step size to obtain the sixth congestion control parameter;
  • the fourth acquiring unit 604 is further configured to acquire a sixth traffic characteristic, where the sixth traffic characteristic includes statistical information generated when the second device forwards traffic according to the sixth congestion control parameter in the second cycle;
  • the fifth obtaining unit 605 is further configured to obtain a sixth return value according to the sixth flow characteristic
  • the execution unit 606 is further configured to execute the corresponding processing if the sum of the sixth reward value and the second reward value is greater than the sum of the fifth reward value and the first reward value.
  • the execution unit 706 is specifically configured to modify the third congestion control rule according to the fourth step size
  • the execution unit 606 is specifically configured to modify the first congestion control rule according to the first step length.
  • the execution unit 706 is specifically configured to use the second step size to modify the second congestion control parameter to obtain the third congestion control parameter;
  • the execution unit 606 is specifically configured to obtain a third traffic characteristic, where the third traffic characteristic includes statistical information generated when the first device forwards traffic according to the third congestion control parameter in the third period;
  • the execution unit 606 is specifically configured to obtain the third reward value according to the third flow characteristic
  • the execution unit 606 is specifically configured to use the fifth step size to modify the sixth congestion control parameter to obtain the seventh congestion control parameter;
  • the execution unit 606 is specifically configured to obtain a seventh traffic characteristic, where the seventh traffic characteristic includes statistical information generated when the second device forwards traffic according to the seventh congestion control parameter in the third period;
  • the execution unit 606 is specifically configured to obtain the seventh reward value according to the seventh flow characteristic.
  • each unit of the congestion control apparatus is similar to those described in the foregoing embodiments shown in FIG. 2 and FIG. 3 and FIG. 4, and will not be repeated here.
  • FIG. 8 is a schematic structural diagram of an embodiment of the congestion control device provided by this application.
  • the congestion control device 800 includes a processor 810, a memory coupled with the processor 810, and a communication interface 830.
  • the congestion control device 800 may be the network device of FIG. 1, the first device or the second device.
  • the processor 810 may be a central processing unit (CPU), a network processor (NP), or a combination of a CPU and an NP.
  • the processor may also be an application-specific integrated circuit (ASIC), a programmable logic device (PLD), or a combination thereof.
  • ASIC application-specific integrated circuit
  • PLD programmable logic device
  • the above-mentioned PLD may be a complex programmable logic device (CPLD), a field-programmable gate array (FPGA), a generic array logic (GAL) or any combination thereof.
  • the processor 810 may refer to one processor, or may include multiple processors.
  • the memory may include volatile memory (volatile memory), such as random access memory (random access memory, RAM); the memory may also include non-volatile memory (non-volatile memory), such as read-only memory (read-only memory). , ROM), flash memory (flash memory), hard disk drive (HDD) or solid-state drive (SSD); the memory may also include a combination of the above types of memory.
  • volatile memory volatile memory
  • non-volatile memory non-volatile memory
  • read-only memory read-only memory
  • ROM read-only memory
  • flash memory flash memory
  • HDD hard disk drive
  • SSD solid-state drive
  • Computer-readable instructions are stored in the memory.
  • the computer-readable instructions include multiple software modules, such as a first acquisition module 822, a second acquisition module 824, a third acquisition module 826, a fourth acquisition module 828, and a fifth acquisition module. 830, execute module 832.
  • the processor 810 After the processor 810 executes each software module, it can perform corresponding operations according to the instructions of each software module.
  • an operation performed by a software module actually refers to an operation performed by the processor 810 according to an instruction of the software module.
  • the first acquisition module 822 may be configured to acquire a first flow characteristic, the first flow characteristic includes statistical information generated when the first device forwards traffic according to the first congestion control parameter in the first cycle, and the first congestion control parameter is based on the first congestion control parameter. Obtained by congestion control rules.
  • the second obtaining module 824 is configured to obtain the first reward value according to the first traffic characteristic.
  • the third obtaining module 826 is configured to modify the first congestion control parameter by using the first step to obtain the second congestion control parameter.
  • the fourth obtaining module 828 is configured to obtain the second flow characteristic, and the second flow characteristic includes the statistical information generated when the first device forwards the flow according to the second congestion control parameter in the second period.
  • the fifth obtaining module 830 is configured to obtain the second reward value according to the second traffic characteristic.
  • the execution module 832 is configured to execute corresponding processing if the second reward value is greater than the first reward value.
  • the processor 810 executes the computer-readable instructions in the memory, it can perform all operations that can be performed by the network device or the first device or the second device according to the instructions of the computer-readable instructions. The operations performed in the embodiment corresponding to FIG. 3 and FIG. 4.
  • the disclosed system, device, and method can be implemented in other ways.
  • the device embodiments described above are only illustrative.
  • the division of the units is only a logical function division, and there may be other divisions in actual implementation, for example, multiple units or components may be combined or It can be integrated into another system, or some features can be ignored or not implemented.
  • the displayed or discussed mutual coupling or direct coupling or communication connection may be indirect coupling or communication connection through some interfaces, devices or units, and may be in electrical, mechanical or other forms.
  • the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the objectives of the solutions of the embodiments.
  • the functional units in the various embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units may be integrated into one unit.
  • the above-mentioned integrated unit can be implemented in the form of hardware or software functional unit.
  • the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer readable storage medium.
  • the technical solution of the present application essentially or the part that contributes to the existing technology or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium , Including several instructions to make a computer device (which may be a personal computer, a server, or a network device, etc.) execute all or part of the steps of the methods described in the various embodiments of the present application.

Landscapes

  • Engineering & Computer Science (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Environmental & Geological Engineering (AREA)
  • Data Exchanges In Wide-Area Networks (AREA)
PCT/CN2020/113775 2019-12-03 2020-09-07 拥塞控制方法以及相关设备 WO2021109661A1 (zh)

Priority Applications (2)

Application Number Priority Date Filing Date Title
EP20895560.9A EP4054134A4 (de) 2019-12-03 2020-09-07 Überlastungssteuerungsverfahren und zugehörige vorrichtung
US17/831,070 US20220294736A1 (en) 2019-12-03 2022-06-02 Congestion Control Method and Related Device

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
CN201911223339.7A CN112910789A (zh) 2019-12-03 2019-12-03 拥塞控制方法以及相关设备
CN201911223339.7 2019-12-03

Related Child Applications (1)

Application Number Title Priority Date Filing Date
US17/831,070 Continuation US20220294736A1 (en) 2019-12-03 2022-06-02 Congestion Control Method and Related Device

Publications (1)

Publication Number Publication Date
WO2021109661A1 true WO2021109661A1 (zh) 2021-06-10

Family

ID=76104308

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/CN2020/113775 WO2021109661A1 (zh) 2019-12-03 2020-09-07 拥塞控制方法以及相关设备

Country Status (4)

Country Link
US (1) US20220294736A1 (de)
EP (1) EP4054134A4 (de)
CN (1) CN112910789A (de)
WO (1) WO2021109661A1 (de)

Families Citing this family (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20210243125A1 (en) * 2020-01-31 2021-08-05 Hewlett Packard Enterprise Development Lp System and method for avoiding congestion in a computer network
CN113411263B (zh) * 2021-06-18 2023-03-14 中国工商银行股份有限公司 一种数据传输方法、装置、设备及存储介质
CN117544567B (zh) * 2024-01-09 2024-03-19 南京邮电大学 存传一体的rdma数据中心拥塞控制方法

Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20110149730A1 (en) * 2008-06-06 2011-06-23 Gabor Nemeth Technique for improving congestion control
WO2012097737A1 (zh) * 2011-01-18 2012-07-26 华为技术有限公司 一种数据传输控制方法及设备
US20140269326A1 (en) * 2013-03-15 2014-09-18 Google Inc. Dynamic congestion control
CN107079435A (zh) * 2015-05-26 2017-08-18 华为技术有限公司 数据传输装置、v2v通信系统及方法
WO2017161566A1 (zh) * 2016-03-25 2017-09-28 华为技术有限公司 一种拥塞控制方法、装置及相关设备
US10257097B1 (en) * 2016-10-04 2019-04-09 EMC IP Holding Company LLC Connection based selection of a network congestion control process

Family Cites Families (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US7499453B2 (en) * 2000-05-19 2009-03-03 Cisco Technology, Inc. Apparatus and methods for incorporating bandwidth forecasting and dynamic bandwidth allocation into a broadband communication system
WO2011107121A1 (en) * 2010-03-05 2011-09-09 Nec Europe Ltd. A method for operating a wireless network and a wireless network
WO2012019638A1 (en) * 2010-08-09 2012-02-16 Nokia Siemens Networks Oy Increasing efficiency of admission control in a network
US10484257B1 (en) * 2015-07-15 2019-11-19 Amazon Technologies, Inc. Network event automatic remediation service
CN108881056B (zh) * 2017-05-15 2022-02-25 华为技术有限公司 一种拥塞控制方法、网络设备及其网络接口控制器
US10708806B2 (en) * 2018-01-02 2020-07-07 Verizon Patent And Licensing Inc. Systems and methods for a self-organizing network based on user equipment information
CN110278157B (zh) * 2018-03-14 2022-08-09 华为技术有限公司 拥塞控制方法及网络设备
CN110120921B (zh) * 2019-05-13 2022-07-01 深圳市赛为智能股份有限公司 拥塞避免方法、装置、计算机设备及存储介质
WO2021064770A1 (ja) * 2019-09-30 2021-04-08 日本電気株式会社 システム、方法及び制御装置

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20110149730A1 (en) * 2008-06-06 2011-06-23 Gabor Nemeth Technique for improving congestion control
WO2012097737A1 (zh) * 2011-01-18 2012-07-26 华为技术有限公司 一种数据传输控制方法及设备
US20140269326A1 (en) * 2013-03-15 2014-09-18 Google Inc. Dynamic congestion control
CN107079435A (zh) * 2015-05-26 2017-08-18 华为技术有限公司 数据传输装置、v2v通信系统及方法
WO2017161566A1 (zh) * 2016-03-25 2017-09-28 华为技术有限公司 一种拥塞控制方法、装置及相关设备
US10257097B1 (en) * 2016-10-04 2019-04-09 EMC IP Holding Company LLC Connection based selection of a network congestion control process

Non-Patent Citations (3)

* Cited by examiner, † Cited by third party
Title
KONG, JINSHENG: "Intelligent Adaptive Control Approach of Congestion Control for Computer Networks", SYSTEMS ENGINEERING AND ELECTRONICS, vol. 27, no. 7, 1 July 2005 (2005-07-01), pages 1301 - 1303, XP055819294, ISSN: 1001-506x *
NTT DOCOMO, INC.: "Congestion Control for NR Sidelink", 3GPP DRAFT; R1-1906210 CONGESTION CONTROL, 3RD GENERATION PARTNERSHIP PROJECT (3GPP), MOBILE COMPETENCE CENTRE ; 650, ROUTE DES LUCIOLES ; F-06921 SOPHIA-ANTIPOLIS CEDEX ; FRANCE, vol. RAN WG1, no. Reno, USA; 20190513 - 20190517, 3 May 2019 (2019-05-03), Mobile Competence Centre ; 650, route des Lucioles ; F-06921 Sophia-Antipolis Cedex ; France, XP051708249 *
See also references of EP4054134A4

Also Published As

Publication number Publication date
EP4054134A4 (de) 2023-01-11
US20220294736A1 (en) 2022-09-15
CN112910789A (zh) 2021-06-04
EP4054134A1 (de) 2022-09-07

Similar Documents

Publication Publication Date Title
WO2021109661A1 (zh) 拥塞控制方法以及相关设备
KR102478440B1 (ko) 혼잡 제어 방법 및 네트워크 디바이스
JP7451689B2 (ja) ネットワーク輻輳処理方法、モデル更新方法、および関連装置
CN108768876B (zh) 一种面向机器学习框架的流量调度方法
US20220210026A1 (en) Network Parameter Configuration Method and Apparatus, Computer Device, and Storage Medium
US11888744B2 (en) Spin-leaf network congestion control method, node, system, and storage medium
CN110351187B (zh) 数据中心网络中路径切换粒度自适应的负载均衡方法
CN102763385A (zh) 针对数据中心环境优化的通信输送
CN101969408B (zh) 基于分组dscp标记的主动队列管理方法
US20140211625A1 (en) Predictive management of a network buffer
CN112995048B (zh) 数据中心网络的阻塞控制与调度融合方法及终端设备
WO2015044719A1 (en) Apparatus for optimising a configuration of a communications network device
WO2020063299A1 (zh) 统计活跃流数目的方法、网络设备和系统
WO2021047404A1 (zh) 一种网络参数配置方法及装置
CN112422443A (zh) 一种拥塞算法的自适应控制方法、存储介质、设备及系统
CN103888313A (zh) 一种预测流表项的最优超时时间的方法
WO2024012065A1 (zh) 数据传输控制方法、装置、计算机可读存储介质、计算机设备及计算机程序产品
CN118381765B (zh) 无损网络拥塞控制方法、装置、设备、介质及交换机系统
CN115102905B (zh) 一种ecn水线调整方法及装置
CN109698925A (zh) 基于数据驱动的实时视频拥塞控制方法及装置
Zhuo et al. Rack-level congestion control
CN106101005A (zh) 一种数据中心网络中基于分组长度的拥塞控制方法
CN109508433B (zh) 基于匹配算法性能调整的负载波动应对方法和系统
He et al. Improvement of GCC Congestion Control Algorithm in Streaming Media Transmission
CN108737286B (zh) 一种全局拥塞价格的计算方法

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 20895560

Country of ref document: EP

Kind code of ref document: A1

ENP Entry into the national phase

Ref document number: 2020895560

Country of ref document: EP

Effective date: 20220603

NENP Non-entry into the national phase

Ref country code: DE